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aria-label="Breadcrumbs"><ul class="breadcrumbs" itemscope="" itemtype="https://schema.org/BreadcrumbList"><li class="breadcrumbs__item"><a aria-label="Home page" class="breadcrumbs__link" href="/"><svg viewBox="0 0 24 24" class="breadcrumbHomeIcon_YNFT"><path d="M10 19v-5h4v5c0 .55.45 1 1 1h3c.55 0 1-.45 1-1v-7h1.7c.46 0 .68-.57.33-.87L12.67 3.6c-.38-.34-.96-.34-1.34 0l-8.36 7.53c-.34.3-.13.87.33.87H5v7c0 .55.45 1 1 1h3c.55 0 1-.45 1-1z" fill="currentColor"></path></svg></a></li><li class="breadcrumbs__item"><span class="breadcrumbs__link">Operations</span><meta itemprop="position" content="1"></li><li class="breadcrumbs__item"><span class="breadcrumbs__link">Performance tuning</span><meta itemprop="position" content="2"></li><li itemscope="" itemprop="itemListElement" itemtype="https://schema.org/ListItem" class="breadcrumbs__item breadcrumbs__item--active"><span class="breadcrumbs__link" itemprop="name">Segment size optimization</span><meta itemprop="position" content="3"></li></ul></nav><div class="tocCollapsible_ETCw theme-doc-toc-mobile tocMobile_ITEo"><button type="button" class="clean-btn tocCollapsibleButton_TO0P">On this page</button></div><div class="theme-doc-markdown markdown"><header><h1>Segment size optimization</h1></header><p>In Apache Druid, it's important to optimize the segment size because</p><ol><li>Druid stores data in segments. If you're using the <a href="/docs/latest/ingestion/rollup">best-effort roll-up</a> mode, |
| increasing the segment size might introduce further aggregation which reduces the dataSource size.</li><li>When a query is submitted, that query is distributed to all Historicals and realtime tasks |
| which hold the input segments of the query. Each process and task picks a thread from its own processing thread pool |
| to process a single segment. If segment sizes are too large, data might not be well distributed between data |
| servers, decreasing the degree of parallelism possible during query processing. |
| At the other extreme where segment sizes are too small, the scheduling |
| overhead of processing a larger number of segments per query can reduce |
| performance, as the threads that process each segment compete for the fixed |
| slots of the processing pool.</li></ol><p>It would be best if you can optimize the segment size at ingestion time, but sometimes it's not easy |
| especially when it comes to stream ingestion because the amount of data ingested might vary over time. In this case, |
| you can create segments with a sub-optimized size first and optimize them later using <a href="/docs/latest/data-management/compaction">compaction</a>.</p><p>You may need to consider the followings to optimize your segments.</p><ul><li>Number of rows per segment: it's generally recommended for each segment to have around 5 million rows. |
| This setting is usually <em>more</em> important than the below "segment byte size". |
| This is because Druid uses a single thread to process each segment, |
| and thus this setting can directly control how many rows each thread processes, |
| which in turn means how well the query execution is parallelized.</li><li>Segment byte size: it's recommended to set 300 ~ 700MB. If this value |
| doesn't match with the "number of rows per segment", please consider optimizing |
| number of rows per segment rather than this value.</li></ul><div class="theme-admonition theme-admonition-info alert alert--info admonition_LlT9"><div class="admonitionHeading_tbUL"><span class="admonitionIcon_kALy"><svg viewBox="0 0 14 16"><path fill-rule="evenodd" d="M7 2.3c3.14 0 5.7 2.56 5.7 5.7s-2.56 5.7-5.7 5.7A5.71 5.71 0 0 1 1.3 8c0-3.14 2.56-5.7 5.7-5.7zM7 1C3.14 1 0 4.14 0 8s3.14 7 7 7 7-3.14 7-7-3.14-7-7-7zm1 3H6v5h2V4zm0 6H6v2h2v-2z"></path></svg></span>info</div><div class="admonitionContent_S0QG"><p> The above recommendation works in general, but the optimal setting can |
| vary based on your workload. For example, if most of your queries |
| are heavy and take a long time to process each row, you may want to make |
| segments smaller so that the query processing can be more parallelized. |
| If you still see some performance issue after optimizing segment size, |
| you may need to find the optimal settings for your workload.</p></div></div><p>There might be several ways to check if the compaction is necessary. One way |
| is using the <a href="/docs/latest/querying/sql-metadata-tables#system-schema">System Schema</a>. The |
| system schema provides several tables about the current system status including the <code>segments</code> table. |
| By running the below query, you can get the average number of rows and average size for published segments.</p><div class="language-sql codeBlockContainer_Ckt0 theme-code-block" style="--prism-color:#bfc7d5;--prism-background-color:#292d3e"><div class="codeBlockContent_biex"><pre tabindex="0" class="prism-code language-sql codeBlock_bY9V thin-scrollbar"><code class="codeBlockLines_e6Vv"><span class="token-line" style="color:#bfc7d5"><span class="token keyword" style="font-style:italic">SELECT</span><span class="token plain"></span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain"> </span><span class="token string" style="color:rgb(195, 232, 141)">"start"</span><span class="token punctuation" style="color:rgb(199, 146, 234)">,</span><span class="token plain"></span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain"> </span><span class="token string" style="color:rgb(195, 232, 141)">"end"</span><span class="token punctuation" style="color:rgb(199, 146, 234)">,</span><span class="token plain"></span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain"> version</span><span class="token punctuation" style="color:rgb(199, 146, 234)">,</span><span class="token plain"></span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain"> </span><span class="token function" style="color:rgb(130, 170, 255)">COUNT</span><span class="token punctuation" style="color:rgb(199, 146, 234)">(</span><span class="token operator" style="color:rgb(137, 221, 255)">*</span><span class="token punctuation" style="color:rgb(199, 146, 234)">)</span><span class="token plain"> </span><span class="token keyword" style="font-style:italic">AS</span><span class="token plain"> num_segments</span><span class="token punctuation" style="color:rgb(199, 146, 234)">,</span><span class="token plain"></span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain"> </span><span class="token function" style="color:rgb(130, 170, 255)">AVG</span><span class="token punctuation" style="color:rgb(199, 146, 234)">(</span><span class="token string" style="color:rgb(195, 232, 141)">"num_rows"</span><span class="token punctuation" style="color:rgb(199, 146, 234)">)</span><span class="token plain"> </span><span class="token keyword" style="font-style:italic">AS</span><span class="token plain"> avg_num_rows</span><span class="token punctuation" style="color:rgb(199, 146, 234)">,</span><span class="token plain"></span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain"> </span><span class="token function" style="color:rgb(130, 170, 255)">SUM</span><span class="token punctuation" style="color:rgb(199, 146, 234)">(</span><span class="token string" style="color:rgb(195, 232, 141)">"num_rows"</span><span class="token punctuation" style="color:rgb(199, 146, 234)">)</span><span class="token plain"> </span><span class="token keyword" style="font-style:italic">AS</span><span class="token plain"> total_num_rows</span><span class="token punctuation" style="color:rgb(199, 146, 234)">,</span><span class="token plain"></span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain"> </span><span class="token function" style="color:rgb(130, 170, 255)">AVG</span><span class="token punctuation" style="color:rgb(199, 146, 234)">(</span><span class="token string" style="color:rgb(195, 232, 141)">"size"</span><span class="token punctuation" style="color:rgb(199, 146, 234)">)</span><span class="token plain"> </span><span class="token keyword" style="font-style:italic">AS</span><span class="token plain"> avg_size</span><span class="token punctuation" style="color:rgb(199, 146, 234)">,</span><span class="token plain"></span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain"> </span><span class="token function" style="color:rgb(130, 170, 255)">SUM</span><span class="token punctuation" style="color:rgb(199, 146, 234)">(</span><span class="token string" style="color:rgb(195, 232, 141)">"size"</span><span class="token punctuation" style="color:rgb(199, 146, 234)">)</span><span class="token plain"> </span><span class="token keyword" style="font-style:italic">AS</span><span class="token plain"> total_size</span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain"></span><span class="token keyword" style="font-style:italic">FROM</span><span class="token plain"></span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain"> sys</span><span class="token punctuation" style="color:rgb(199, 146, 234)">.</span><span class="token plain">segments A</span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain"></span><span class="token keyword" style="font-style:italic">WHERE</span><span class="token plain"></span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain"> datasource </span><span class="token operator" style="color:rgb(137, 221, 255)">=</span><span class="token plain"> </span><span class="token string" style="color:rgb(195, 232, 141)">'your_dataSource'</span><span class="token plain"> </span><span class="token operator" style="color:rgb(137, 221, 255)">AND</span><span class="token plain"></span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain"> is_published </span><span class="token operator" style="color:rgb(137, 221, 255)">=</span><span class="token plain"> </span><span class="token number" style="color:rgb(247, 140, 108)">1</span><span class="token plain"></span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain"></span><span class="token keyword" style="font-style:italic">GROUP</span><span class="token plain"> </span><span class="token keyword" style="font-style:italic">BY</span><span class="token plain"> </span><span class="token number" style="color:rgb(247, 140, 108)">1</span><span class="token punctuation" style="color:rgb(199, 146, 234)">,</span><span class="token plain"> </span><span class="token number" style="color:rgb(247, 140, 108)">2</span><span class="token punctuation" style="color:rgb(199, 146, 234)">,</span><span class="token plain"> </span><span class="token number" style="color:rgb(247, 140, 108)">3</span><span class="token plain"></span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain"></span><span class="token keyword" style="font-style:italic">ORDER</span><span class="token plain"> </span><span class="token keyword" style="font-style:italic">BY</span><span class="token plain"> </span><span class="token number" style="color:rgb(247, 140, 108)">1</span><span class="token punctuation" style="color:rgb(199, 146, 234)">,</span><span class="token plain"> </span><span class="token number" style="color:rgb(247, 140, 108)">2</span><span class="token punctuation" style="color:rgb(199, 146, 234)">,</span><span class="token plain"> </span><span class="token number" style="color:rgb(247, 140, 108)">3</span><span class="token plain"> </span><span class="token keyword" style="font-style:italic">DESC</span><span class="token punctuation" style="color:rgb(199, 146, 234)">;</span><br></span></code></pre><div class="buttonGroup__atx"><button type="button" aria-label="Copy code to clipboard" title="Copy" class="clean-btn"><span class="copyButtonIcons_eSgA" aria-hidden="true"><svg viewBox="0 0 24 24" class="copyButtonIcon_y97N"><path fill="currentColor" d="M19,21H8V7H19M19,5H8A2,2 0 0,0 6,7V21A2,2 0 0,0 8,23H19A2,2 0 0,0 21,21V7A2,2 0 0,0 19,5M16,1H4A2,2 0 0,0 2,3V17H4V3H16V1Z"></path></svg><svg viewBox="0 0 24 24" class="copyButtonSuccessIcon_LjdS"><path fill="currentColor" d="M21,7L9,19L3.5,13.5L4.91,12.09L9,16.17L19.59,5.59L21,7Z"></path></svg></span></button></div></div></div><p>Please note that the query result might include overshadowed segments. |
| In this case, you may want to see only rows of the max version per interval (pair of <code>start</code> and <code>end</code>).</p><p>Once you find your segments need compaction, you can consider the below two options:</p><ul><li>Turning on the <a href="/docs/latest/design/coordinator#automatic-compaction">automatic compaction of Coordinators</a>. |
| The Coordinator periodically submits <a href="/docs/latest/ingestion/tasks#compact">compaction tasks</a> to re-index small segments. |
| To enable the automatic compaction, you need to configure it for each dataSource via Coordinator's dynamic configuration. |
| For more information, see <a href="/docs/latest/data-management/automatic-compaction">Automatic compaction</a>.</li><li>Running periodic Hadoop batch ingestion jobs and using a <code>dataSource</code> |
| inputSpec to read from the segments generated by the Kafka indexing tasks. This might be helpful if you want to compact a lot of segments in parallel. |
| Details on how to do this can be found on the <a href="/docs/latest/data-management/update">Updating existing data</a> section |
| of the data management page.</li></ul><h2 class="anchor anchorWithStickyNavbar_LWe7" id="learn-more">Learn more<a href="#learn-more" class="hash-link" aria-label="Direct link to Learn more" title="Direct link to Learn more"></a></h2><ul><li>For an overview of compaction and how to submit a manual compaction task, see <a href="/docs/latest/data-management/compaction">Compaction</a>.</li><li>To learn how to enable and configure automatic compaction, see <a href="/docs/latest/data-management/automatic-compaction">Automatic compaction</a>.</li></ul></div></article><nav class="pagination-nav docusaurus-mt-lg" aria-label="Docs pages"><a class="pagination-nav__link pagination-nav__link--prev" href="/docs/latest/operations/basic-cluster-tuning"><div class="pagination-nav__sublabel">Previous</div><div class="pagination-nav__label">Basic cluster tuning</div></a><a class="pagination-nav__link pagination-nav__link--next" href="/docs/latest/operations/mixed-workloads"><div class="pagination-nav__sublabel">Next</div><div class="pagination-nav__label">Mixed workloads</div></a></nav></div></div><div class="col col--3"><div class="tableOfContents_bqdL thin-scrollbar theme-doc-toc-desktop"><ul class="table-of-contents table-of-contents__left-border"><li><a href="#learn-more" class="table-of-contents__link toc-highlight">Learn more</a></li></ul></div></div></div></div></main></div></div><footer class="footer"><div class="container container-fluid"><div class="footer__bottom text--center"><div class="margin-bottom--sm"><img src="/img/favicon.png" class="themedImage_ToTc themedImage--light_HNdA footer__logo"><img src="/img/favicon.png" class="themedImage_ToTc themedImage--dark_i4oU footer__logo"></div><div class="footer__copyright">Copyright © 2023 Apache Software Foundation. Except where otherwise noted, licensed under CC BY-SA 4.0. Apache Druid, Druid, and the Druid logo are either registered trademarks or trademarks of The Apache Software Foundation in the United States and other countries.</div></div></div></footer></div> |
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